从 Pandas DataFrame 返回单个单元格值

Question

我想问一个关于此线程的扩展问题：

Select rows from a DataFrame based on values in a column in pandas.

该线程的代码如下：

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(),
               'B': 'one one two three two two one three'.split(),
               'C': np.arange(8), 'D': np.arange(8) * 2})
print(df)
#      A      B  C   D
# 0  foo    one  0   0
# 1  bar    one  1   2
# 2  foo    two  2   4
# 3  bar  three  3   6
# 4  foo    two  4   8
# 5  bar    two  5  10
# 6  foo    one  6  12
# 7  foo  three  7  14

print(df.loc[df['D'] == 14])

这将产生以下结果：

   A    B      C   D
7  foo  three  7  14

根据上面的代码，我怎样才能返回单个“值”而不是一行。也就是说，如何返回值 '7' 或值 'foo' 而不是整行？

Answer 1

@JonahWilliams 很接近，这是一个有效的：

import pandas as pd
import numpy as np
df = pd.DataFrame({'A': 'foo bar foo bar foo bar foo foo'.split(),
               'B': 'one one two three two two one three'.split(),
               'C': np.arange(8), 'D': np.arange(8) * 2})

print(df.loc[df['D'] == 14]['A'].index.values)

>>>[7]

print(df.loc[df['D'] == 14]['A'].values)

>>>['foo']